Remote sensing diagnosis of ecosystem resilience dynamics in agricultural heritage landscapes

This dataset supports the publication “Remote sensing diagnosis of ecosystem resilience dynamics in agricultural heritage landscapes”. It provides processed remote sensing products, derived indicators, and analysis codes used to quantify and map ecosystem resilience across polder-based agricultural heritage landscapes in the Taihu Basin, China, from 2005 to 2024.
The dataset includes:
EVI Time Series (2005–2024):
A long-term Enhanced Vegetation Index (EVI) dataset derived from MODIS imagery.LSWI Time Series (2005–2024):
A Land Surface Water Index (LSWI) time series produced from MODIS surface reflectance data to capture spatiotemporal variations in surface moisture and hydrological dynamics relevant to agricultural resilience.Long-term Resilience Indicator:
Pixel-wise resilience metrics estimated from EVI time series using autoregressive modeling (AR(1)) and recovery trajectory analysis to capture long-term stability and recovery capacity.Short-term Resilience Index:
Disturbance–recovery responses computed over short temporal windows to detect transient resilience fluctuations following perturbations.Environmental Drivers Dataset:
Spatial layers representing key environmental and anthropogenic factors influencing resilience.R Code for Indicator Calculation:
Scripts used for preprocessing, resilience computation, and visualization. All analyses were performed in R (v4.3.2) using packages raster, dplyr, mgcv, and ggplot2.